Beyond Gaze Points: Augmenting Eye Movement with Brainwave Data for Multimodal User Authentication in Extended Reality
arxiv(2024)
摘要
The increasing adoption of Extended Reality (XR) in various applications
underscores the need for secure and user-friendly authentication methods.
However, existing methods can disrupt the immersive experience in XR settings,
or suffer from higher false acceptance rates. In this paper, we introduce a
multimodal biometric authentication system that combines eye movement and
brainwave patterns, as captured by consumer-grade low-fidelity sensors. Our
multimodal authentication exploits the non-invasive and hands-free properties
of eye movement and brainwaves to provide a seamless XR user experience and
enhanced security as well. Using synchronized eye and brainwave data collected
from 30 participants through consumer-grade devices, we investigated whether
twin neural networks can utilize these biometrics for identity verification.
Our multimodal authentication system yields an excellent Equal Error Rate (EER)
of 0.298%, which means an 83.6% reduction in EER compared to the single eye
movement modality or a 93.9% reduction in EER compared to the single brainwave
modality.
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